Logic programming reveals alteration of key transcription factors in multiple myeloma

Abstract Innovative approaches combining regulatory networks (RN) and genomic data are needed to extract biological information for a better understanding of diseases, such as cancer, by improving the identification of entities and thereby leading to potential new therapeutic avenues. In this study,...

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Autores principales:	Bertrand Miannay, Stéphane Minvielle, Olivier Roux, Pierre Drouin, Hervé Avet-Loiseau, Catherine Guérin-Charbonnel, Wilfried Gouraud, Michel Attal, Thierry Facon, Nikhil C Munshi, Philippe Moreau, Loïc Campion, Florence Magrangeas, Carito Guziolowski
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a8448570cfee4cc69771d5a8924d77e8
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spelling	oai:doaj.org-article:a8448570cfee4cc69771d5a8924d77e82021-12-02T12:32:20ZLogic programming reveals alteration of key transcription factors in multiple myeloma10.1038/s41598-017-09378-92045-2322https://doaj.org/article/a8448570cfee4cc69771d5a8924d77e82017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-09378-9https://doaj.org/toc/2045-2322Abstract Innovative approaches combining regulatory networks (RN) and genomic data are needed to extract biological information for a better understanding of diseases, such as cancer, by improving the identification of entities and thereby leading to potential new therapeutic avenues. In this study, we confronted an automatically generated RN with gene expression profiles (GEP) from a cohort of multiple myeloma (MM) patients and normal individuals using global reasoning on the RN causality to identify key-nodes. We modeled each patient by his or her GEP, the RN and the possible automatically detected repairs needed to establish a coherent flow of the information that explains the logic of the GEP. These repairs could represent cancer mutations leading to GEP variability. With this reasoning, unmeasured protein states can be inferred, and we can simulate the impact of a protein perturbation on the RN behavior to identify therapeutic targets. We showed that JUN/FOS and FOXM1 activities are altered in almost all MM patients and identified two survival markers for MM patients. Our results suggest that JUN/FOS-activation has a strong impact on the RN in view of the whole GEP, whereas FOXM1-activation could be an interesting way to perturb an MM subgroup identified by our method.Bertrand MiannayStéphane MinvielleOlivier RouxPierre DrouinHervé Avet-LoiseauCatherine Guérin-CharbonnelWilfried GouraudMichel AttalThierry FaconNikhil C MunshiPhilippe MoreauLoïc CampionFlorence MagrangeasCarito GuziolowskiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bertrand Miannay Stéphane Minvielle Olivier Roux Pierre Drouin Hervé Avet-Loiseau Catherine Guérin-Charbonnel Wilfried Gouraud Michel Attal Thierry Facon Nikhil C Munshi Philippe Moreau Loïc Campion Florence Magrangeas Carito Guziolowski Logic programming reveals alteration of key transcription factors in multiple myeloma
description	Abstract Innovative approaches combining regulatory networks (RN) and genomic data are needed to extract biological information for a better understanding of diseases, such as cancer, by improving the identification of entities and thereby leading to potential new therapeutic avenues. In this study, we confronted an automatically generated RN with gene expression profiles (GEP) from a cohort of multiple myeloma (MM) patients and normal individuals using global reasoning on the RN causality to identify key-nodes. We modeled each patient by his or her GEP, the RN and the possible automatically detected repairs needed to establish a coherent flow of the information that explains the logic of the GEP. These repairs could represent cancer mutations leading to GEP variability. With this reasoning, unmeasured protein states can be inferred, and we can simulate the impact of a protein perturbation on the RN behavior to identify therapeutic targets. We showed that JUN/FOS and FOXM1 activities are altered in almost all MM patients and identified two survival markers for MM patients. Our results suggest that JUN/FOS-activation has a strong impact on the RN in view of the whole GEP, whereas FOXM1-activation could be an interesting way to perturb an MM subgroup identified by our method.
format	article
author	Bertrand Miannay Stéphane Minvielle Olivier Roux Pierre Drouin Hervé Avet-Loiseau Catherine Guérin-Charbonnel Wilfried Gouraud Michel Attal Thierry Facon Nikhil C Munshi Philippe Moreau Loïc Campion Florence Magrangeas Carito Guziolowski
author_facet	Bertrand Miannay Stéphane Minvielle Olivier Roux Pierre Drouin Hervé Avet-Loiseau Catherine Guérin-Charbonnel Wilfried Gouraud Michel Attal Thierry Facon Nikhil C Munshi Philippe Moreau Loïc Campion Florence Magrangeas Carito Guziolowski
author_sort	Bertrand Miannay
title	Logic programming reveals alteration of key transcription factors in multiple myeloma
title_short	Logic programming reveals alteration of key transcription factors in multiple myeloma
title_full	Logic programming reveals alteration of key transcription factors in multiple myeloma
title_fullStr	Logic programming reveals alteration of key transcription factors in multiple myeloma
title_full_unstemmed	Logic programming reveals alteration of key transcription factors in multiple myeloma
title_sort	logic programming reveals alteration of key transcription factors in multiple myeloma
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/a8448570cfee4cc69771d5a8924d77e8
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Logic programming reveals alteration of key transcription factors in multiple myeloma

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